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Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology (e.g., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed an in-silico model of a synthetic microbial consortia of sucrose-secreting Synechococcus elongatus PCC 7942 and Escherichia coli W. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function. Author summary: Microbial communities, play important, yet poorly understood roles in health and agriculture. As we develop a better understanding of how these communities interact together, as well as with their host organisms, there is growing interest in engineering communities with specific functions, such as for treating disease, personalized probiotics, or aiding plants with nutrient uptake. To better understand how these microbes interact with each other, we want to monitor the exchange of metabolites and the locations of the microbes, tasks which at present are technically challenging, if not impossible. Where experimental approaches for monitoring metabolites are limited, computational tools can enable greater access to the fate of both chemicals and microbes within a community. In this study, we developed a computerized model of a synthetic microbial community of two bacteria, one which performs photosynthesis and supplies sugar and another which consumes the sugar for growth. We showed that the relative level of sugar secretion regulates not only the steady-state support for the consumer partner's growth, but also how the community changes with time. To determine the importance of spatial organization within the community, we fit a model and used it to predict colony growth. We anticipate that the synergy between experimental and computational approaches will improve our ability to design microbial communities with new functions. [ABSTRACT FROM AUTHOR]

Bacterial microcompartments (BMC) are complex macromolecular assemblies that participate in varied chemical processes in about one fourth of bacterial species. BMC-encapsulated enzymatic activities are segregated from other cell contents by means of semipermeable shells, justifying why BMC are viewed as prototype nano-reactors for biotechnological applications. Herein, we undertook a comparative study of bending propensities of BMC hexamers (BMC-H), the most abundant shell constituents. Published data show that some BMC-H, like β-carboxysomal CcmK, tend to assemble flat whereas other BMC-H often build curved objects. Inspection of available crystal structures presenting BMC-H in tiled arrangements permitted us to identify two major assembly modes with a striking connection with experimental trends. All-atom molecular dynamics (MD) supported that BMC-H bending is triggered robustly only from the arrangement adopted in crystals by BMC-H that experimentally form curved objects, leading to very similar arrangements to those found in structures of recomposed BMC shells. Simulations on triplets of planar-behaving hexamers, which were previously reconfigured to comply with such organization, confirmed that bending propensity is mostly defined by the precise lateral positioning of hexamers, rather than by BMC-H identity. Finally, an interfacial lysine was pinpointed as the most decisive residue in controlling PduA spontaneous curvature. Globally, results presented herein should contribute to improve our understanding of the variable mechanisms of biogenesis characterized for BMC, and of possible strategies to regulate BMC size and shape. Author summary: Bacterial microcompartments are complex macromolecular ensembles that participate in varied metabolic processes in many microorganisms. They consist of a proteinaceous shell that encapsulates enzymatic cargo that mediate connected chemical reactions. Being confined within shells, the overall efficiency of the process is thought to augment, and reactions that imply toxic intermediates, which are lethal to the host in free-diffusing context, become feasible. These natural nano-reactors are therefore appealing for biotechnology purposes. Understanding how such complex objects form is essential. Experimental studies demonstrated the existence of two possible pathways. Thus, shell components grew onto a preformed core of organized cargo in cyanobacterial carboxysomes, whereas in Pdu compartments, both cargo and shell formation seemed to occur randomly. With the aim to contribute to the understanding of the different biogenesis pathways, here we investigated the trend of the most abundant protein constituents of bacterial micro-compartment shells to form curved structures. We first discovered the occurrence of two major assembly modes in deposited BMC-H crystal structures that clustered proteins in two groups that correlate well to their experimental propensities to form bent or flat structures. Subsequently, molecular dynamic simulations supported that only one of the modes is ready to curve. Moreover, simulations on protein mutants pinpointed a residue that seems to be pivotal in triggering bending. Globally, our data permit to draw a scenario that explains BMC biogenesis differences as a result of the capture of some BMC-H, such as CcmK of carboxysomes, in local minima corresponding to flat states that would delay closure of BMC shells, something that might require the intervention of other molecular effectors. [ABSTRACT FROM AUTHOR]

The recent explosion of interest and advances in machine learning technologies has opened the door to new analytical capabilities in microbiology. Using experimental data such as images or videos, machine learning, in particular deep learning with neural networks, can be harnessed to provide insights and predictions for microbial populations. This paper presents such an application in which a Recurrent Neural Network (RNN) was used to perform prediction of microbial growth for a population of two Pseudomonas aeruginosa mutants. The RNN was trained on videos that were acquired previously using fluorescence microscopy and microfluidics. Of the 20 frames thatmake up each video, 10 were used as inputs to the network which outputs a prediction for the next 10 frames of the video. The accuracy of the network was evaluated by comparing the predicted frames to the original frames, as well as population curves and the number and size of individual colonies extracted from these frames. Overall, the growth predictions are found to be accurate in metrics such as image comparison, colony size, and total population. Yet, limitations exist due to the scarcity of available and comparable data in the literature, indicating a need for more studies. Both the successes and challenges of our approach are discussed. [ABSTRACT FROM AUTHOR]

Using density functional theory with an accurate treatment of van der Waals interactions, we investigate the enantioselective recognition and separation of chiral molecules on stepped metal surfaces. Our calculations demonstrate that the separation ability of metal substrates can be significantly enhanced by surface decoration and external strain. For example, applying 2% tensile strain to the Ag-alloyed Au(532) surface leads to a dramatic increase (by 89%) in cysteine enantioselectivity as compared to that of pristine Au(532). Analysis on the computed binding energies shows that the interaction energy is the predominant factor that affects the separation efficiency in strongly bound systems. Our study presents a new strategy to modify the enantioselectivity of stepped metal surfaces and paves the way for exploring high efficiency chiral separation technology in pharmaceutical industry. [ABSTRACT FROM AUTHOR]

The structure, tautomeric preferences, base-pairing ability, stacking interactions and HOMO-LUMO gaps of the naphtho-homologated DNA bases are studied using theoretical techniques. The bases have structures similar to the benzo-fused predecessors and show a tautomeric preference to naphtho-thymine and naphtho-adenine resulting in formation of hydrogen-bonded dimers.

The effect of the insertion/addition of a benzene ring to the natural nucleic acid bases on the local aromaticity of the so-called size-expanded (xN, with N being adenine, guanine, cytosine, and thymine) bases is studied. The results reveal notable differences in the aromatic character of the natural and size-expanded bases, which generally are hardly affected upon hydrogen bonding.

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea. We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py. Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology. [ABSTRACT FROM AUTHOR]

We investigate the possibility of tailoring the electronic properties of isoreticular metal-organic materials by replacing the metal atom in the metal-organic cluster and by doping. The electronic structure of M-IRMOF1, where IRMOF1 stands for isoreticular metal-organic framework 1 and M=Be, Mg, Ca, Zn, and Cd, was examined using density-functional theory. The results show that these materials have similar band gaps (ca. 3.5 eV) and a conduction band that is split into two bands, the lower of which has a width that varies with metal substitution. This variation prompted us to investigate whether doping with Al or Li could be used to tailor the electronic properties of the Zn-IRMOF1 and Be-IRMOF1 materials. It is shown that replacing one metal atom with Al can effectively be used to create IRMOFs with different metallic properties. On the other hand, adding Li produces structural changes that render this approach less suitable. [ABSTRACT FROM AUTHOR]

Molecular dynamics simulations of the DNA duplex d(CCAACGTTGG)2 were used to study the relationship between DNA sequence and structure in a crystal environment. Three different force fields were used: a traditional description based on atomic point charges, a polarizable force field, and an “extra-point” force field (with additional charges on extranuclear sites). It is found that all the force fields reproduce fairly well the sequence-dependent features of the experimental structure. The polarizable force field, however, provides the most accurate representation of the crystal structure and the sequence-dependent effects observed in the experiment. These results point out to the need of the inclusion of polarization for accurate descriptions of DNA. © 2004 American Institute of Physics. [ABSTRACT FROM AUTHOR]

The results from investigation of the electronic properties of an xDNA duplex made of natural and benzo-homologated bases and a natural one with an analogous sequence suggest that xDNA has a smaller [pi]-[pi]* gap than B-DNA suggests and could be used as plausible candidate for molecular-wire applications.

A comprehensive ab initio study is used to observe and analyze the structure, stability and electronic properties of guanine-zinc-cytosine (G-Zn-C) base pair, which when combined with metals like Zn and Co lead to the formation of M-DNA at high values of pH. The analysis suggest that a lot of things should be taken care of while studying the electronic properties of such base-pairs, as M-DNAs with functionals do not account for strong electronic correlations.

Second-order Moller-Plesset perturbation theory and density functional theory (DFT) are used to investigate the structural and electronic properties of size-expanded DNA bases, xA, xC, xG, and xT, and their natural counterparts. The results show that natural and size-expanded bases have both nonplanar amino groups, but the latter also has nonplanar aromatic rings, and xG is easier to oxidize than G.

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models. [ABSTRACT FROM AUTHOR]

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as "building blocks" for a range of customized intracellular scaffolds. We summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering. [ABSTRACT FROM AUTHOR]

The self-assembly properties of N(9)-(2,3-dihydroxypropyl adenine) (DHPA), a plausible prebiotic nucleoside analogue of adenosine, were investigated using density functional theory. Two different isomers were considered, and it is found that while both isomers can form a variety of structures, including chains, one of them is also able to form cages and helixes. When these results were put in the context of substrate supported molecular self-assembly, it is concluded that gas-phase self-assembly studies that consider isomer identity and composition not only can aid interpreting the experimental results, but also reveal structures that might be overlooked otherwise. In particular, this study suggest that a double-helical structure made of DHPA molecules which could have implications in prebiotic chemistry and nanotechnology, is stable even at room temperature. For example electrical properties (energy gap of 4.52eV) and a giant permanent electrical dipole moment (49.22 Debye) were found in our larger double-helical structure (3.7 nm) formed by 14 DHPA molecules. The former properties could be convenient for construction of organic dielectric-based devices. [ABSTRACT FROM AUTHOR]

Despite extensive investigation using hydrodynamic models and experiments over the past decades, there remain open questions regarding the origin of the initial rupture of thin liquid films. One of the reasons that makes it difficult to identify the rupture origin is the coexistence of two dewetting mechanisms, namely, thermal nucleation and spinodal instability, as observed in many experimental studies. Using a coarse-grained model and large-scale molecular dynamics simulations, we are able to characterize the very early stage of dewetting in nanometer-thick liquid-metal films wetting a solid substrate. We observe the features characteristic of both spinodal instability and thermal nucleation in the spontaneously dewetting films and show that these two macroscopic mechanisms share a common origin at molecular levels. [ABSTRACT FROM AUTHOR]

We demonstrate a controllable surface-coordinated linear polymerization of long-chain poly(phenylacetylenyl)s that are self-organized into a "circuit-board" pattern on a Cu(100) surface. Scanning tunneling microscopy/spectroscopy (STM/S) corroborated by ab initio calculations, reveals the atomistic details of the molecular structure, and provides a clear signature of electronic and vibrational properties of the poly(phenylacetylene)s chains. Notably, the polymerization reaction is confined epitaxially to the copper lattice, despite a large strain along the polymerized chain that subsequently renders it metallic. Polymerization and depolymerization reactions can be controlled locally at the nanoscale by using a charged metal tip. This control demonstrates the possibility of precisely accessing and controlling conjugated chain-growth polymerization at low temperature. This finding may lead to the bottom-up design and realization of sophisticated architectures for molecular nano-devices. [ABSTRACT FROM AUTHOR]

Thin-film dewetting can be exploited to self-assemble and organize nanoparticles. Crucial to this effort is the understanding of the nanoscale liquid phase dynamics, and molecular dynamics simulations (MD) provide a powerful tool in this respect. In this paper we demonstrate that MD simulations utilizing a Lennard-Jones (LJ) interface potential can be effectively used to study various wetting regimes of nanoscale Cu disks on graphite. It was found that both the dewetting velocity and the equilibrium contact angle increase with a decrease in the Cu-C potential, and that the retraction velocities obtained are characteristic of dewetting phenomena governed by inertial and capillary forces. This phenomena leads to a change in morphology, from disks to nanodroplets, which, in turn, when using the most accurate LJ potential, jump off the graphitic substrate with a velocity on the order of 140 m/s. This ejection velocity is consistent with the previous experimental observation that nanoscale Au triangles deposited on graphite or glass jump when exposed to a pulsed laser above the melting threshold. Interestingly, the Cu ejection velocity decreases when the liquid Cu disks are deposited on a suspended graphene membrane. Finally, a Rayleigh-Plateau-like instability, which leads to the breakup of a pseudo-one-dimensional liquid Cu nanowire in nanodroplets, is revealed when the MD simulations are performed using different LJ interface potentials. [ABSTRACT FROM AUTHOR]

In order to test the feasibility of using metal-organic frameworks (MOFs) to pre-concentrate explosive molecules for detection, molecular simulations of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) within IRMOF-1 were performed. Grand canonical Monte Carlo (GCMC) simulations were used to generate adsorption isotherms for pure RDX, RDX in dry air, and RDX in wet air. In addition to the isotherms, the GCMC simulations provide adsorption energies and density distributions of the adsorbates within the MOF. Molecular dynamics simulations calculate diffusivities and provide a detailed understanding of the change in conformation of the RDX molecule upon adsorption. The presence of dry air has little influence on the amount of RDX that adsorbs. The presence of wet air increases the amount of RDX that adsorbs due to favourable interactions between RDX and water. We found a Henry's law constant of 21.2 mol/kg/bar for both pure RDX and RDX in dry air. The RDX adsorption sites are located (i) in big cages, (ii) near a vertex, and (iii) between benzene rings. The energy of adsorption of RDX at infinite dilution was found to be - 9.2 kcal/mol. The distributions of bond lengths, bond angles and torsion angles in RDX are uniformly slightly broader in the gas phase than in the adsorbed phase, but not markedly so. The self-diffusivity of RDX in IRMOF-1 is a strong function of temperature, with an activation energy of 6.0 kcal/mol. [ABSTRACT FROM AUTHOR]

Size-expanded DNA bases are analogues of natural bases that can be described as a synthesis between benzene and a natural base. Size-expanded bases have been combined with natural bases to form xDNA and yDNA, a new class of synthetic nucleic acids. We are interested in xDNA and yDNA because they might function as molecular wires. Recently, we also became intrigued by the possibility of altering the electronic conductivity of xDNA and yDNA by means of structural changes in the constituent bases. This possibility appeared after we noticed that the highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO–LUMO) gap of the base yG can be increased dramatically, ∼0.73 eV, by changing the aromaticity of its benzene ring. Therefore, if one is able to alter the HOMO–LUMO gap of size-expanded bases, it should be possible to change the electronic conductivity of xDNAs and yDNAs as well. In the present work, we extend our study on aromaticity-induced changes on the electronic properties of size-expanded bases by investigating the HOMO–LUMO gap of all possible tautomers of xC. We have found that, as for yG, the HOMO–LUMO gap of xC can be modified by ∼ 0.74 eV, and that this can be accomplished by changing the aromaticity of its benzene ring. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2006 [ABSTRACT FROM AUTHOR]

Quantum chemical calculations reveal that neither steric hindrance nor less polar solvent medium is able to reduce the otherwise high hydrolysis rate of arsenate-esters. These results question the stability of As-DNA not only in aqueous but also in non-aqueous environments. [ABSTRACT FROM AUTHOR]

The behavior of a 50 nm Cu-Ni alloy film on Si in a process of reactive solid-state dewetting is presented. The films were annealed at a range of temperatures (300-700 °C) in 1% H2 99% N2 reducing atmosphere. The resulting alloy and silicide particles formed by film dewetting and film reaction with the substrate were distinguished by selective wet etching and examined by scanning electron microscopy and spectroscopy. After potassium hydroxide etch, regions that etch slower than silicon substrate have distribution statistics similar to the alloy and silicide particles prior to their removal, indicating strong coupling between mass transport across the interface and along the surface. [ABSTRACT FROM AUTHOR]

Self-assembly is a spontaneous process through which macroscopic structures are formed from basic microscopic constituents (e.g., molecules or colloids). By contrast, the formation of large biological molecules inside the cell (such as proteins or nucleic acids) is a process more akin to self-organization than to self-assembly, as it requires a constant supply of external energy. Recent studies have tried to merge self-assembly with self-organization by analyzing the assembly of self-propelled (or active) colloid-like particles whose motion is driven by a permanent source of energy. Here we present evidence that points to the fact that self-propulsion considerably enhances the assembly of polymers: self-propelled molecules are found to assemble faster into polymer-like structures than non self-propelled ones. The average polymer length increases towards a maximum as the self-propulsion force increases. Beyond this maximum, the average polymer length decreases due to the competition between bonding energy and disruptive forces that result from collisions. The assembly of active molecules might have promoted the formation of large pre-biotic polymers that could be the precursors of the informational polymers we observe nowadays. [ABSTRACT FROM AUTHOR]